1. Field
The field relates to image identification.
2. Background Art
Video content is increasingly popular and easy to publish and distribute to users. Video content can now be viewed on a variety of different devices using a variety of different video players. Video content can be provided on tape, memory, storage disks (e.g., DVDs), or other storage media. Video content is often streamed or downloaded over computer networks, such as, the Internet or other networks. The World Wide Web further supports the publication and distribution of video content. A number of different publishers increasingly serve or publish video content online to remote users. Online sites, such as Hulu.com and youtube.com, that allow users to view video legally are some of the most popular on the Web.
With this increase in the volume and popularity of video it is even more desirable to identify and prevent illegal copying and distribution of video content (also called videos). Current techniques to identify illegal video copies are limited. For example, with existing techniques, an attacker can prevent a probe video from matching the reference videos by modifying the probe video. For instance, current existing techniques are not robust to transformations involving recompression, rotation, stretching, scaling or flipping.
An example of an existing technique is YouTube's ContentID system that attempts to match videos that are visually similar. At its core, it compares probe video frames against a collection of reference video frames. The comparison is done by comparing the Hamming distance between fingerprints of the video frames.
However, techniques are still needed that are robust against transformation involving recompression, rotation, stretching, scaling or flipping.